Events & Calendars Statistics & Data Science Colloquium: Scott LaCombe

This project incorporates policy volatility to our understanding of the relationship between public opinion and policy. Given increasing levels of polarization between Republicans and Democrats, there are growing fears of policy leapfrogging voters and governments oscillating from being too conservative to too liberal. I argue a way to understand policy representation and responsiveness is to model just mean changes in policy, but also to incorporate the variance of policy changes to understand what causes some states to see large shifts in policy, while others remain relatively stable. I use a heteroskedastic regression to estimate responsiveness and policy volatility in the states and find that
institutional configurations that prioritize a strong checks and balance system can keep states more tightly bound to public opinion, while others allow for more volatile policy outputs that may be less responsive to the average voter. Adding volatility into models of responsiveness is an important step in understanding what drives the relationship between public opinion and policy.
This project incorporates policy volatility to our understanding of the relationship between public opinion and policy. Given increasing levels of polarization between Republicans and Democrats, there are growing fears of policy leapfrogging voters and governments oscillating from being too conservative to too liberal. I argue a way to understand policy representation and responsiveness is to model just mean changes in policy, but also to incorporate the variance of policy changes to understand what causes some states to see large shifts in policy, while others remain relatively stable. I use a heteroskedastic regression to estimate responsiveness and policy volatility in the states and find that
institutional configurations that prioritize a strong checks and balance system can keep states more tightly bound to public opinion, while others allow for more volatile policy outputs that may be less responsive to the average voter. Adding volatility into models of responsiveness is an important step in understanding what drives the relationship between public opinion and policy.